Abstract
<p align="justify">Handwriting refers to the result of writing by hand (not typed). The writing style of people are not the same. One of the United Nations official languages, Arabic, has a numerical system known as Arabic (Indian) numeral. The identification of feature help humans to be able distinguish the patterns. The grouping patterns can be applied to the machine for recognizing object in the image. Connected component labeling is used for separating characters to be easily recognizable. K- nearest neighbors is used to find the similarity value between query image and template images are based on the nearest neighbors class. This analytical study was tested using 100 test images. The top three classification results of Arabic (Indian) handwritten recognition use k- nearest neighbors (KNN) are 86% when k = 1, 84% when k = 3, and 83% with k = 5.</p>
Highlights
Tulisan tangan merupakan hasil menulis, dengan tangan
Handwriting refers to the result of writing by hand
Connected component labeling is used for separating characters to be recognizable
Summary
Tulisan tangan merupakan hasil menulis, barang yang ditulis ataupun cara menulis dengan tangan (bukan ketikan) [1]. Bahasa Arab, walaupun menggunakan sistem penomoran yang sama, namun bentuk karakter angka yang digunakan berbeda dari angka modern yang dipakai saat ini. Studi Analisis Pengenalan Pola Tulisan Tangan Angka Arabic (Indian) Menggunakan Metode K- Nearest Neighbors dan Connected Component Labeling – [Roni Akbar, dkk]. Template matching adalah salah satu metode yang dapat digunakan dalam tahapan terakhir pengenalan pola, yakni tahapan klasifikasi. Segmentasi digunakan untuk memisahkan karakter yang ada pada citra agar tidak bergabung satu sama lain. Connected component labeling merupakan metode segmentasi untuk memisahkan objek dan tidak terpengaruh pada kemiringan objek [8]. Pada tulisan ini dikaji studi analisis pengenalan pola tulisan tangan menggunakan metode k-nearest neighbors dan connected component labeling. Diharapkan studi analisis ini dapat mengenali dan mengklasifikasikan nilai tulisan tangan berupa objek dari bahasa negara lain, yakni angka Arabic (Indian) dengan metode k- nearest neighbors
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